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Agent skill

Bilibili RAG Local

by via007 in via007/bilibili-rag

使用本地 Bilibili RAG 服务进行检索与问答。用户询问 B 站收藏夹内容、视频要点总结、来源追溯、入库状态时使用。内容问答时优先通过 sessionid 与 folderids 限定范围，避免空范围导致 fallback。

Apache-2.0Auto-check passedAI & LLM Engineering

Install Bilibili RAG Local

skills CLI
$ npx skills add via007/bilibili-rag --skill bilibili-rag-local -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install via007/bilibili-rag bilibili-rag-local --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/via007/bilibili-rag.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/bilibili-rag-local .claude/skills/bilibili-rag-local && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
bilibili-rag-local
GitHub stars
1.3k
Token cost
~326 tokens
SKILL.md length
98 words
Files
1
Skills in repo
1
Repo updated
First seen
Licence
Apache-2.0

At a glance

使用本地 Bilibili RAG 服务进行检索与问答。用户询问 B 站收藏夹内容、视频要点总结、来源追溯、入库状态时使用。内容问答时优先通过 sessionid 与 folderids 限定范围，避免空范围导致 fallback。

  • Works in 2 steps: 检查服务可达：优先调用 GET /knowledge/stats。 → 若不可达，明确提示“本地服务未启动或端口不是 8000”，不要编造结果。
  • Tasks that involve Retrieval-augmented generation
  • SKILL.md covers 执行前检查, 会话与范围（关键）, 主要能力 and 返回格式要求, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Bilibili RAG Local is an agent skill from via007/bilibili-rag. 使用本地 Bilibili RAG 服务进行检索与问答。用户询问 B 站收藏夹内容、视频要点总结、来源追溯、入库状态时使用。内容问答时优先通过 sessionid 与 folderids 限定范围，避免空范围导致 fallback。

Its SKILL.md is about 330 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in AI & LLM Engineering, covering Retrieval-augmented generation. It works with Bilibili and Qwen. The repository describes itself as: B站收藏夹RAG知识库：收藏不吃灰，B 站收藏夹 → 语音转写 → 向量检索 → 对话问答. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Retrieval-augmented generation

Example prompts

  • “/bilibili-rag-local”

Workflow steps

2 steps, taken from the first numbered list in SKILL.md.

  1. 检查服务可达：优先调用 GET /knowledge/stats。
  2. 若不可达，明确提示“本地服务未启动或端口不是 8000”，不要编造结果。

What it can do on your machine

Read from SKILL.md and the folder at commit 79a9b33. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Bilibili RAG Local loads about 326 tokens when it runs. Until then it costs about 34 tokens; SKILL.md has 98 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~34
When it runs · the whole SKILL.md, loaded when a task matches
~326

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from via007/bilibili-rag at commit 79a9b33, republished under its Apache-2.0 licence (© via007). 98 words, ~326 tokens.

Download SKILL.mdSave it as .claude/skills/bilibili-rag-local/SKILL.md (or your agent's skills folder).
name
bilibili-rag-local
description
使用本地 Bilibili RAG 服务进行检索与问答。用户询问 B 站收藏夹内容、视频要点总结、来源追溯、入库状态时使用。内容问答时优先通过 session_id 与 folder_ids 限定范围，避免空范围导致 fallback。

Bilibili RAG Local

面向本地运行的 bilibili-rag 服务（默认 http://127.0.0.1:8000）。

执行前检查

  1. 检查服务可达：优先调用 GET /knowledge/stats。
  2. 若不可达，明确提示“本地服务未启动或端口不是 8000”，不要编造结果。

会话与范围（关键）

  1. 执行 /chat/ask 前，先确保拿到 session_id。
  2. 使用 GET /knowledge/folders/status?session_id=<session_id> 获取可用 media_id 列表，并作为 folder_ids 传入。
  3. 内容类问题调用 /chat/ask 时，默认必须传：question + session_id + folder_ids，不要传空 folder_ids。
  4. 若缺少 session_id 或 folder_ids，先向用户索取或先查状态接口，不要直接调用无范围问答。

主要能力

  1. 检索片段：调用 POST /chat/search?query=<问题>&k=5。
  2. 问答总结：调用 POST /chat/ask，请求体优先包含： question、session_id、folder_ids。
  3. 入库状态：调用 GET /knowledge/folders/status?session_id=<session_id>。

返回格式要求

  1. 先给结论，再给证据。
  2. 证据优先来自接口返回的 sources 或 search results。
  3. 每条证据给出 title + url，必要时补充 bvid。
  4. 当 /chat/ask 返回 sources=[] 或无召回时，明确说明可能是会话无范围或未入库，并提示检查 session_id/folder_ids 与同步状态。

交互策略

  1. 用户是闲聊或无关问题时，简短回复后再引导回收藏夹知识问答。
  2. 用户问题具体且与视频内容相关时，优先调用“带范围参数”的 /chat/ask，不要只按标题猜测回答。
  3. /chat/search 仅用于补充证据或列候选，不要替代最终问答结论。

安全边界

  1. 不输出任何 Cookie、Token、SESSDATA 等敏感信息。
  2. 不执行与本地 bilibili-rag 无关的高风险系统命令。
  3. 仅使用用户本机可访问的服务地址，不主动访问未知公网接口。

© via007, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/bilibili-rag-local of via007/bilibili-rag.

Open the folder on GitHubat commit 79a9b33

Compare with similar skills

Bilibili RAG Local next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Bilibili RAG Local compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Bilibili RAG Local this skillvia007/bilibili-rag1.3k—~326Automated safety check: PassApache-2.0
Local AI Agentsmicrosoft/ai-agents-for-beginners77k—~1.3kAutomated safety check: PassMIT
Local AI Agentsmicrosoft/ai-agents-for-beginners77k—~1.4kAutomated safety check: PassMIT
Aliyun Qwen Rerankcinience/alicloud-skills397—~291Automated safety check: PassMIT
Local AI Agentsmicrosoft/ai-agents-for-beginners77k—~1.7kAutomated safety check: PassMIT
Bili NoteRimagination/bili-note322—~3.6kAutomated safety check: PassMIT

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Works with

Categories

Questions about Bilibili RAG Local

What does Bilibili RAG Local do?

使用本地 Bilibili RAG 服务进行检索与问答。用户询问 B 站收藏夹内容、视频要点总结、来源追溯、入库状态时使用。内容问答时优先通过 sessionid 与 folderids 限定范围，避免空范围导致 fallback。. Bilibili RAG Local is an agent skill from via007/bilibili-rag.

When should I use Bilibili RAG Local?

Bilibili RAG Local fits situations like: tasks that involve Retrieval-augmented generation.

How do I install Bilibili RAG Local in Claude Code?

Run `npx skills add via007/bilibili-rag --skill bilibili-rag-local -a claude-code`. Or copy the skill folder (skills/bilibili-rag-local in via007/bilibili-rag) into .claude/skills/bilibili-rag-local in your project. Claude Code loads it when a task matches its description.

How do I install Bilibili RAG Local in Codex?

Run `npx skills add via007/bilibili-rag --skill bilibili-rag-local -a codex`. Or copy the skill folder (skills/bilibili-rag-local in via007/bilibili-rag) into .agents/skills/bilibili-rag-local in your project. Codex loads it when a task matches its description.

Can I use Bilibili RAG Local in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add via007/bilibili-rag --skill bilibili-rag-local -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/bilibili-rag-local, .gemini/skills/bilibili-rag-local, .github/skills/bilibili-rag-local and .opencode/skills/bilibili-rag-local in your project.

What does Bilibili RAG Local need to run?

SKILL.md names no scripts, command-line tools or credentials: Bilibili RAG Local is instructions for the agent only.

Does Bilibili RAG Local access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Bilibili RAG Local safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Bilibili RAG Local use?

Bilibili RAG Local is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Bilibili RAG Local use?

About 326 tokens (SKILL.md is roughly 1.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Bilibili RAG Local?

Skills that share tags, products or a category with Bilibili RAG Local: Local AI Agents (microsoft/ai-agents-for-beginners, 77k stars), Local AI Agents (microsoft/ai-agents-for-beginners, 77k stars), Aliyun Qwen Rerank (cinience/alicloud-skills, 397 stars) and Local AI Agents (microsoft/ai-agents-for-beginners, 77k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Bilibili RAG Local?

via007 (a GitHub user) maintains it in via007/bilibili-rag, which has 1,338 GitHub stars. The repository was last updated on September 27, 2026.

Source: via007/bilibili-rag on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.